A Beginner's Guide to Dataform: Getting Started with Your First Deployment
Are you excited to start your journey in Dataform? Are you ready to unleash the power of automated data pipelines? Then look no further because in this beginner's guide, we're going to walk you through the basics of Dataform and how to get started with your first deployment.
What is Dataform?
But why use Dataform over other tools such as Airflow or dbt? Unlike these tools, Dataform is a cloud-native platform that requires no infrastructure management. This means you can focus on your data instead of managing your infrastructure. Additionally, Dataform integrates seamlessly with common cloud data warehouses such as BigQuery, Redshift, and Snowflake.
Getting Started with Your First Deployment
Now that you know what Dataform is, let's get started with your first deployment. In this section, we'll walk you through the steps of setting up your Dataform account and deploying your first project.
Setting up Your Dataform Account
The first step in deploying your first project is to set up your Dataform account. To do this, head over to dataform.co and click on "Start for Free." You'll be prompted to sign up using either Google or GitHub. Once you've signed up, you'll be taken to the Dataform dashboard.
Creating Your First Project
Once you've set up your account, you can create your first project. To do this, click on "New Project" from the dashboard. You'll be prompted to enter a project name and description. You can choose to make your project either public or private.
Creating Your First Table
After you've created your project, the next step is to create your first table. To do this, click on "New File" from the project dashboard. You'll be prompted to enter a file name and description.
Dataform uses SQL to create tables, so if you're familiar with SQL, this step should be a breeze. If not, don't worry! Dataform has a powerful code editor that makes writing SQL easy. Here's an example of a simple table:
SUM(order_total) AS revenue
This table aggregates order data by customer ID and order date. Note that we're using the
GROUP BY clause to group the data by customer and date.
Creating Your First Transformation
Once you've created your table, the next step is to create a transformation. Transformations are SQL scripts that modify your data in some way. They can be used to clean your data, join multiple tables together, or perform complex aggregations.
To create a transformation, click on "New File" again and select "Transformation" as the file type. Here's an example of a simple transformation:
DATE_TRUNC('month', order_date) AS order_month,
SUM(order_total) AS revenue
This transformation adds a new column to our table that truncates the order date to the month level. We're using the
DATE_TRUNC function to do this.
Testing Your Project
Now that you've created your table and transformation, it's time to test your project. To do this, click on "Deploy" from the project dashboard. Dataform will lint your code and check for syntax errors.
Assuming everything looks good, click on "Deploy" again to deploy your project. Dataform will create a new schema in your data warehouse and create your table and transformation.
Finally, it's time to test your project! To do this, click on "Run" from the project dashboard. Dataform will execute your transformation and display the results in the console.
Congratulations! You've just deployed your first Dataform project.
In this beginner's guide, we've walked you through the basics of Dataform and how to get started with your first deployment. We've covered setting up your Dataform account, creating your first project, and creating your first table and transformation.
But this is just the beginning. Dataform is a powerful tool with endless possibilities. We encourage you to experiment with different SQL transformations, explore the advanced features of Dataform, and join the community of Dataform users.
So what are you waiting for? Start your journey in Dataform today and unlock the power of automated data pipelines.
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